In [9]:
import matplotlib.pyplot as plt
import numpy as np
# base info
print("Dataset Info:")
print(f"Train dataset size: {len(train_dataset)}")
print(f"Validation dataset size: {len(validation_dataset)}")
print(f"Test dataset size: {len(test_dataset)}")
# class names
class_names = train_dataset.class_names
print("\nClass names:", class_names)
# image counts
def count_images_per_class(dataset):
counts = {name: 0 for name in class_names}
for images, labels in dataset:
for label in labels:
counts[class_names[label.numpy()]] += 1
return counts
train_counts = count_images_per_class(train_dataset)
print("\nImages per class in training set:", train_counts)
# check some images
plt.figure(figsize=(10, 10))
for images, labels in train_dataset.take(1):
for i in range(9):
plt.subplot(3, 3, i + 1)
plt.imshow(images[i].numpy().astype("uint8"))
plt.title(class_names[labels[i]])
plt.axis("off")
plt.show()
# image statistics
def analyze_image_statistics(dataset):
pixel_mean = []
pixel_std = []
for images, _ in dataset:
pixel_mean.append(tf.reduce_mean(images))
pixel_std.append(tf.math.reduce_std(images))
return {
'mean': tf.reduce_mean(pixel_mean),
'std': tf.reduce_mean(pixel_std)
}
stats = analyze_image_statistics(train_dataset)
print("\nImage Statistics:")
print(f"Mean pixel value: {stats['mean']:.2f}")
print(f"Std pixel value: {stats['std']:.2f}")
# show images
plt.figure(figsize=(10, 5))
plt.bar(class_names, list(train_counts.values()))
plt.title('Number of Images per Class')
plt.ylabel('Count')
plt.show()
# check batch shape
for image_batch, labels_batch in train_dataset.take(1):
print("\nImage batch shape:", image_batch.shape)
print("Labels batch shape:", labels_batch.shape)
Dataset Info:
Train dataset size: 63
Validation dataset size: 32
Test dataset size: 63
Class names: ['cat', 'dog']
Images per class in training set: {'cat': 1000, 'dog': 1000}
2024-11-23 12:20:16.308261: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int32 and shape [2000]
[[{{node Placeholder/_4}}]]
2024-11-23 12:20:16.308825: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_0' with dtype string and shape [2000]
[[{{node Placeholder/_0}}]]
Image Statistics: Mean pixel value: 113.95 Std pixel value: 65.51
2024-11-23 12:20:20.350424: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int32 and shape [2000]
[[{{node Placeholder/_4}}]]
2024-11-23 12:20:20.351295: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_4' with dtype int32 and shape [2000]
[[{{node Placeholder/_4}}]]
Image batch shape: (32, 180, 180, 3) Labels batch shape: (32,)
